load packages
```r
library(ggplot2)
library(data.table)
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Registered S3 method overwritten by ‘data.table’: method from
print.data.table
data.table 1.14.2 using 1 threads (see ?getDTthreads). Latest news:
r-datatable.com ********** This installation of data.table has not
detected OpenMP support. It should still work but in single-threaded
mode. This is a Mac. Please read https://mac.r-project.org/openmp/. Please engage with
Apple and ask them for support. Check r-datatable.com for updates, and
our Mac instructions here: https://github.com/Rdatatable/data.table/wiki/Installation.
After several years of many reports of installation problems on Mac,
it’s time to gingerly point out that there have been no similar problems
on Windows or Linux. **********
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```r
```r
library(stringr)
library(dplyr)
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Attaching package: ‘dplyr’
The following objects are masked from ‘package:data.table’:
between, first, lastThe following objects are masked from ‘package:stats’:
filter, lagThe following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
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```r
```r
library(tibble)
library(here)
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here() starts at /Users/u241374/mike_tisza/teddy_virome/teddy_vir_bac_marker_geneR
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```r
```r
library(rprojroot)
library(ggpubr)
library(rstatix)
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Attaching package: ‘rstatix’
The following object is masked from ‘package:stats’:
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set paths and filenames
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```r
```r
### files
long_table=sprintf(\%s/data/mp142_TGVG1.1_MPA4_combined_abundance_table_longform1.tsv\, find_rstudio_root_file())
metadata_table=sprintf(\%s/data/some_teddy_MP142_metadata2.all_samples1.delivery.csv\, find_rstudio_root_file())
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load long table and metadata, merge
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```r
```r
long_dt <- fread(sprintf(\%s\, long_table), sep = \\t\, header = T) %>%
select(sampleID, rel_abundance, lineage) %>%
mutate(kingdom = case_when(grepl(\k__Bac\, lineage) ~ \Bacteria\,
grepl(\k__Vir\, lineage) ~ \Virus\,
grepl(\k__Ar\, lineage) ~ \Archea\,
grepl(\k__Euk\, lineage) ~ \Eukaryota\,
TRUE ~ \other\))
meta_dt <- fread(sprintf(\%s\, metadata_table), sep = \`summarise()` has grouped output by 'lineage', 'kingdom'. You can override using the `.groups` argument.```r
persist_dt <- merge(persist_dt, mask_id_count, by = \mask_id\) %>%
mutate(frequency_detected = samples_detected/total_samples)
dim(
persist_dt %>% distinct(mask_id)
)
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[1] 555 1
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calculate stats
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```r
```r
stat.test <- persist_dt %>%
filter(kingdom == \Virus\ | kingdom == \Bacteria\) %>%
wilcox_test(frequency_detected ~ kingdom) %>%
add_significance(p.col=\p\, output.col=\p.signif\)
stat.test <- stat.test %>% add_xy_position(x = \kingdom\)
stat.testNA
NA
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<